The shortage of traditional energy sources and environmental pollution caused by the consumption of fossil fuels have become increasingly prominent, and many countries regard the development of ...renewable energy as important for ensuring energy conservation and emission reductions. In addition, renewable portfolio standard is important for China to achieve energy transition. The Chinese government is actively promoting the construction of a renewable portfolio standard system. Considering different renewable energy development targets for renewable portfolio standards, this paper establishes a dynamic computable general equilibrium (CGE) model to research the impacts of achieving various policy targets. The main simulation results are as follows. Promoting renewable sources would have a slightly negative impact on macroeconomics. For each additional percentage point in the share of renewable energy generation in 2030, the loss of GDP would increase by approximately 9.11 billion RMB. A renewable energy policy could be also conducive to carbon emission reduction and energy structure adjustment. Certainly, the proportion of renewable energy in the total power generation should be approximately 34% to achieve the government target for non-fossil fuels to account for approximately 20% of the primary energy consumption by 2030.
•Renewable energy policy would have a slight negative impact on the macroeconomic.•The carbon emissions will be reduced by about 314.29 to 1,525.07 million tons.•Electricity price will be increased under renewable energy policy.•The proportion of renewable energy in total power generation should be about 34% in 2030.
Herein, we demonstrate the use of heterostructures comprised of Co/β‐Mo2C@N‐CNT hybrids for the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in an alkaline electrolyte. The ...Co can not only create a well‐defined heterointerface with β‐Mo2C but also overcomes the poor OER activity of β‐Mo2C, thus leading to enhanced electrocatalytic activity for HER and OER. DFT calculations further proved that cooperation between the N‐CNTs, Co, and β‐Mo2C results in lower energy barriers of intermediates and thus greatly enhances the HER and OER performance. This study not only provides a simple strategy for the construction of heterostructures with nonprecious metals, but also provides in‐depth insight into the HER and OER mechanism in alkaline solution.
That's evolution: Heterostructures composed of Co/β‐Mo2C@N‐CNTs showed high performance for HER and OER in an alkaline electrolyte. The Co nanoparticles not only create a well‐defined heterointerface with β‐Mo2C, but also overcome the poor OER activity of β‐Mo2C, thus leading to enhanced electrocatalytic activity for HER and OER. DFT calculations showed that cooperation by the N‐CNTs, Co, and β‐Mo2C lowers the energy barriers of intermediates.
The goal of semantic segmentation is to segment the input image according to semantic information and predict the semantic category of each pixel from a given label set. With the gradual ...intellectualization of modern life, more and more applications need to infer relevant semantic information from images for subsequent processing, such as augmented reality, autonomous driving, video surveillance, etc. This paper reviews the state-of-the-art technologies of semantic segmentation based on deep learning. Because semantic segmentation requires a large number of pixel-level annotations, in order to reduce the fine-grained requirements of annotation and reduce the economic and time cost of manual annotation, this paper studies the works on weakly-supervised semantic segmentation. In order to enhance the generalization ability and robustness of the segmentation model, this paper investigates the works on domain adaptation in semantic segmentation. Many types of sensors are usually equipped in some practical applications, such as autonomous driving and medical image analysis. In order to mine the association between multi-modal data and improve the accuracy of the segmentation model, this paper investigates the works based on multi-modal data fusion semantic segmentation. The real-time performance of the model needs to be considered in practical application. This paper analyzes the key factors affecting the real-time performance of the segmentation model and investigates the works on real-time semantic segmentation. Finally, this paper summarizes the challenges and promising research directions of semantic segmentation tasks based on deep learning.
Conducting polymers, such as the p-doped poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS), have enabled the development of an array of opto- and bio-electronics devices. However, ...to make these technologies truly pervasive, stable and easily processable, n-doped conducting polymers are also needed. Despite major efforts, no n-type equivalents to the benchmark PEDOT:PSS exist to date. Here, we report on the development of poly(benzimidazobenzophenanthroline):poly(ethyleneimine) (BBL:PEI) as an ethanol-based n-type conductive ink. BBL:PEI thin films yield an n-type electrical conductivity reaching 8 S cm
, along with excellent thermal, ambient, and solvent stability. This printable n-type mixed ion-electron conductor has several technological implications for realizing high-performance organic electronic devices, as demonstrated for organic thermoelectric generators with record high power output and n-type organic electrochemical transistors with a unique depletion mode of operation. BBL:PEI inks hold promise for the development of next-generation bioelectronics and wearable devices, in particular targeting novel functionality, efficiency, and power performance.
As the largest carbon emissions source sector, electric power industry is undoubtedly a principal part of the carbon trading market in China. Aimed at researching the impact on power industry beyond ...establishing the national carbon trading market, a dynamic computable general equilibrium (CGE) model embedded with carbon trading block is introduced in this paper. Subsequently, we design 8 scenarios of which illustrate corresponding industry carbon emissions baselines and free quotas ratios. The main simulation results are as follows. The implementation of carbon emissions trading would bring a certain negative impact on the overall economy. Real GDP will be reduced by about 0.08%–0.52% in 2030. Though low free quotas ratio will cause a relatively high loss of GDP, this negative impact would be eliminated in the long run. In addition, carbon emissions trading would also promote the clean production of electricity. Indeed, the electric power industry would reach carbon emissions peak around 2020. Relative to scenarios without carbon trading, carbon emissions would reduce more than 1000 million tons in 2030 when industry carbon emissions baseline declines at an annual rate of 2%. Consequently, the carbon market can achieve a more significant reduction in carbon emissions with the influencing of quotas fully auctioned scenario.
•A dynamic computable general equilibrium model embedded with carbon trading block is introduced.•Carbon trading policy will promote the optimization and upgrade of industrial structure in power industry.•The demand for electricity in the whole society will decrease under ETS.•Carbon emissions in electric power industry will peak around 2020.
The construction of multi‐stereocenters by a transition metal‐catalyzed cross‐coupling reaction is a major challenge. The catalytic desymmetric functionalization of unactivated alkenes remains ...largely unexplored. Herein, we disclose ‐a desymmetric dicarbofunctionalization of 1,6‐dienes via a nickel‐catalyzed reductive cross‐coupling reaction. The leverage of the underdeveloped chiral 8‐Quinox enables the Ni‐catalyzed desymmetric carbamoylalkylation of both unactivated mono‐ and disubstituted alkenes to form pyrrolidinone bearing two nonadjacent stereogenic centers in high enantio‐ and stereoselectivitives with broad functional‐group tolerance. The synthetic application of pyrrolidinones allows the rapid access to complex chiral fused‐heterocycles.
The desymmetric dicarbofunctionalization of unactivated alkenes by a nickel‐catalyzed reductive cross‐coupling reaction has been developed to access pyrrolidinones bearing multi‐stereocenters with broad functional‐group tolerance. The utilization of the 8‐Quinox ligand is crucial for maintaining high enantio‐ and stereoselectivities.
Comprehensive Summary
The conversion of CF3‐alkenes to gem‐difluoroalkenes using reductive cross‐coupling strategy has received much attention in recent years, however, the use of green and readily ...available reducing salt to mediate these reactions remains to be explored. In this work, a concise construction of gem‐difluoroalkenes, which requires neither a catalyst nor a metal reducing agent, was established. Rongalite, a safe and inexpensive industrial product, was employed as both a radical initiator and reductant. This procedure was compatible with both linear and cyclic diaryliodonium salts, enabling a wide variety of substrates (>70 examples). The utility of this approach was demonstrated through gram‐scale synthesis and efficient late‐stage functionalizations of anti‐inflammatory drugs.
A transition‐metal‐free allylic defluorination reductive cross‐coupling between CF3‐alkenes and diaryliodonium salts mediated by rongalite has been described for the first time. This procedure was compatible with both linear and cyclic diaryliodonium salts, enabling a wide variety of substrates. The utility of this approach was demonstrated through gram‐scale synthesis and efficient late‐stage functionalizations of anti‐inflammatory drugs.
This paper investigates the strategies for adopting blockchain technology in the fresh product supply chain (FPSC) consisting of a supplier, a third-party logistics service provider (3PL) and an ...e-tailer. We analyse the optimal strategies of FPSC members under the benchmark scenario where the FPSC does not adopt blockchain technology and those under the three scenarios where the supplier, 3PL and e-tailer lead the construction of the blockchain-based traceability system (BTS), respectively. We find that adopting blockchain technology is not always the optimal decision for the FPSC, which is related to the consumers' acceptance degree for the product without blockchain technology, the deterioration rate of the fresh product and the allocation proportion of traceability cost of FPSC members when adopting blockchain technology. Regardless of the power and status of each member in the FPSC, it can lead the construction of the BTS. From the perspective of whole FPSC's profit maximisation, the leader of the FPSC should lead the construction of the BTS under the coordination of a two-part tariff contract. This study provides valuable insights for FPSCs to adopt blockchain technology.
This paper proposes a resilient controller for DC microgrid to achieve current sharing and voltage restoration under discrete-time false data injection (FDI) and denial-of-service (DoS) attacks. ...Switching and impulsive signals are used to model the dynamic system of DC microgrid under DoS and FDI. To deal with the cyber attacks, a combined error of current and voltage is proposed and a switching secondary controller is designed. Based on the stability analysis method on hybrid systems, we establish a sufficient condition for selecting control parameters in relation to the average dwell time of FDI attack and the normal communication rate under DoS attack. Furthermore, an adaptive gain based control scheme is proposed to relax the requirement on knowledge of the cyber attacks in control parameter design. The utility of the results is illustrated through case studies on a tested DC microgrid.
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